The pharmaceutical industry continuously pursues new drug treatment options that are more effective, more specific or have fewer adverse side effects than currently administered drugs. Drug therapy alternatives are constantly being developed because genetic variability within the human population results in substantial differences in the effectiveness of many drugs. Therefore, although a wide variety of drug therapy options are currently available, more therapies are always needed in the event that a patient fails to respond.
Traditionally, the treatment paradigm used by physicians has been to prescribe a first-line drug therapy that results in the highest success rate possible for treating a disease. Alternative drug therapies are then prescribed if the first is ineffective. This paradigm is clearly not the best treatment method for certain diseases. For example, in diseases such as cancer, the first treatment is often the most important and offers the best opportunity for successful therapy, so there exists a heightened need to chose an initial drug that will be the most effective against that particular patient's disease.
It is anticipated that there will be 207,090 new female breast cancer diagnoses in the US this year and 39,840 female breast cancer related deaths (American Cancer Society: Cancer Facts and FIGS. 2010). Standard chemotherapy typically includes direct DNA damaging agents such as anthracyclines and alkylating agents as well as antimetabolites and antimicrotubule agents.
Ovarian cancer is the leading cause of death among all gynecological cancers in western countries. This high death rate is due to the diagnosis at an advanced stage in most patients. Epithelial ovarian cancer (EOC) constitutes 90% of ovarian malignancies and is classified into distinct histologic categories including serous, mucinous, endometrioid, clear cell, transitional, mixed, and undifferentiated subtypes. There is increasing evidence that these differed histologies arise from different aetiologies. The current standard treatment for ovarian cancer is debulking surgery and standard platinum taxane based cytotoxic chemotherapy. However, not all patients respond to this, and of those that do, approximately 70% will experience a recurrence. Specific targeted therapies for ovarian cancer based on histological or molecular classification have not yet reached the marketplace. Similarly for other types of cancer, there is still no accurate way of selecting appropriate cytotoxic chemotherapeutic agents.
The advent of microarrays and molecular genomics has the potential for a significant impact on the diagnostic capability and prognostic classification of disease, which may aid in the prediction of the response of an individual patient to a defined therapeutic regimen. Microarrays provide for the analysis of large amounts of genetic information, thereby providing a genetic fingerprint of an individual. There is much enthusiasm that this technology will ultimately provide the necessary tools for custom-made drug treatment regimens.
Currently, healthcare professionals have few mechanisms to help them identify cancer patients who will benefit from chemotherapeutic agents. Identification of the optimal first-line drug has been difficult because methods are not available for accurately predicting which drug treatment would be the most effective for a particular cancer's physiology. This deficiency results in relatively poor single agent response rates and increased cancer morbidity and death. Furthermore, patients often needlessly undergo ineffective, toxic drug therapy.
Molecular markers have been used to select appropriate treatments, for example, in breast cancer. Breast tumors that do not express the estrogen and progesterone hormone receptors as well as the HER2 growth factor receptor, called “triple negative”, appear to be responsive to PARP-1 inhibitor therapy (Linn, S. C., and Van't Veer, L., J. Eur J Cancer 45 Suppl 1, 11-26 (2009); O'Shaughnessy, J., et al. N Engl J Med 364, 205-214 (2011). Recent studies indicate that the triple negative status of a breast tumor may indicate responsiveness to combination therapy including PARP-1 inhibitors, but may not be sufficient to indicate responsiveness to individual PARP-1 inhibitors. (O'Shaughnessy et al., 2011).
Furthermore, there have been other studies that have attempted to identify gene classifiers associated with molecular subtypes to indicate responsiveness of chemotherapeutic agents (Farmer et al. Nat Med 15, 68-74 (2009); Konstantinopoulos, P. A., et al., J Clin Oncol 28, 3555-3561 (2010)). However, to date there does not exist a diagnostic test that works across cancer diseases to accurately define a molecular subtype that demonstrates a deficiency in DNA damage repair, that can also predict sensitivity to any drug that directly or indirectly targets DNA damage repair across diseases.
What is therefore needed is a test that identifies DNA repair deficient tumors with sufficient accuracy to allow the stratification of patients into those who are likely to respond to chemotherapeutic agents that damage DNA, and those who should receive alternative therapies.
What is also needed is a molecular subtype classifier that is predictive of therapeutic responsiveness across different cancer types with sufficient accuracy.